Key Setup Parameters for Meaningful Vibration Data Analysis Dennis H. Shreve Commtest Inc. Knoxville, TN
Meaningful Vibration Data Analysis • Lots of tools and techniques available. • Sometimes can be a bit intimidating and burdensome. • Need to take away some of the mystery. • Make the best of the situation. • Examine scientific terminology and industry jargon.
Getting Down to Basics • Vibration is a leading indicator of machinery health. • Accelerometer is like a doctor’s stethoscope. • Capture the raw data. • Convert to a “signature” for comparison. • Know the equipment make-up. • Watch for patterns, amplitudes, and changes over time. (Interpret information relative to PF curve)
Predictive Maintenance (PdM) (an evolution from Breakdown to Preventive) • 4 Key Elements to the process: – Detection – Analysis – Correction – Verification • Pinpoint a problem, get to the root cause, take action, and verify effectiveness.
DETECTION • Capture details on equipment and application. • Choose the right sensor. • Set up the right measurement parameters. • Obtain good, solid data – also, repeatable.
ANALYSIS • Examine trends, changes, patterns, and amplitudes. (The “Signature”.) • Compare to known acceptable standards or baselines. (Note: Signature, Spectrum, and FFT (Fast Fourier Transform) are used synonymously.)
CORRECTION • Take actions against offending vibration levels: Balancing. Alignment. Replacing defective bearings. Tying down loose components. Avoiding resonance. The BIG 5!
VERIFICATION • Perform a “Before and After” assessment. • Did the follow-up action make the situation better? • If the problem has been addressed, set a new measurement baseline for the future.
Primary Goals of the PdM Program • Ensure convenient rework. • Avoid panic. • Avoid secondary damage. • Promote safety. • Reduce repair time. • Avoid any unnecessary downtime.
12 Steps for Success • Survey the plant in terms of critical, essential, balance of plant categories. • Choose the machines to put into the program. • Optimize measurements in terms of parameters and timing. Choose the method and educate participants . • • Set criteria (alarms) for assessment. • Baseline the machine under consideration. • thru 10, Setup, Measure, Store, Present (detection) . • Problem assessment (analysis) . Correct the fault (correction) . • (After step 12, the process can be re-entered at step 6.)
Establishing the Program • Put equipment into categories of “critical”, “essential”, and “balance of plant”. • Start with the critical machinery. • Get into the physical make-up of the equipment and the application. • Decide the kinds of measurements and sensors to be used. • Look for vibration presence, patterns, and severity.
Vibration measurement • Choose the best location. • Choose the proper sensor. • Make the proper placement – firm mounting and direction. (similar to sensitive directional microphone). • Measure in several axes. • Set measurement parameters to get “tell-tale” data. • Set alarm limits for proper assessment. (typically “warning”, “alert”, and “danger”).
Other Key Considerations … • Know the make-up of the machine in terms of bearings, gearbox, pulleys, couplings, cooling fans (# of blades) and pumps (# of impellor blades). • Know the 1X (i.e., running speed) of the machine being measured. • Know the relative phase readings on key positions of the machine. (This will show relative motion.)
Key Measurement Parameters • Time or frequency data to be captured. • Sample time. • Number of samples. • Number of averages. • Frequency range. • Frequency resolution.
Data Interpretation • Examining presence, patterns, and severity will lead to correction. • There are typically 5 main causes for the vibration: – Unbalance. – Misalignment. – Bearing defects. – Looseness. – Resonance.
Getting Good Data • Avoid the GIGO (garbage in, garbage out) principle. • Make certain to have a good sensor, cabling, and connections. • Ensure proper (solid) mounting (no rocking). • Set up instrument parameters to get the right measurements. • Make sure that the equipment is running. • Be sure that it is the right location. • Recognize “bad” data before moving on. • Utilize auxiliary tools available to build confidence in the assessment. (Examples here include bump tests, coastdown, cross-channel phase, and demodulation.)
Measurement Considerations • Right place, right time. • Minimize outside influences. • Time or frequency? • Frequency band, Fmin and Fmax. • Resolution. • Windowing. • Sampling time. • Number of samples. • Number of averages • Accompanying speed and phase information? • Additional simultaneous channel?
Measurement Relationships • Highest frequency (Fmax) Fmax (Hz) = # of samples / (2.56 * sample time) (corollary: sample time = # lines of resolution / Fmax (Hz)) • Lines of resolution # Lines = samples / 2.56 (corollary: samples = 2.56 * # lines) 4 averages, no overlap • Time for collection Time = (# averages * # lines) / Fmax (in Hz) 4 averages, 50% overlap • Frequency resolution Resolution = Fmax / # lines (Keep in mind the specifications for the sensor and instrumentation.)
Measurement Considerations • Shannon (Nyquist) Sampling Theorem: Sampled signal can be completely reproduced if sampling frequency is at least twice the highest frequency content. (We use the factor 2.56 in digitizing.) • Any attempt to do less results in “aliasing”. • There is an inverse relationship between time sample and highest frequency content. • More samples, less time results in higher frequency.
Digital Sampling… Example Two very different signals with same sampling. The more samples, the better reconstruction. 2.56X is a nice sampling factor in digitizing.
Further considerations • Product(s) specifications and limitations. • Measurement capture. • Measurement processing. • Measurement unit (acceleration, velocity, displacement). • Measurement scaling (rms, average, peak, pk- pk).
Windowing for sampling Comparison of non-periodic sine wave and FFT with leakage (left) to windowed sine wave and FFT showing no leakage (right).
Overlapping Averages Overlap processing shortens the acquisition time by recovering a portion of each previous frame that otherwise is lost due to the effect of the FFT window,
Example – at instrument side Key settings to address
Example – at instrument side Most commonly used On routine data collection Advanced analysis
FFT (Spectrum) Measurement Typical Settings Menu
TWF (Time Waveform) Measurement Typical Settings Menu
Measurements at Instrument Time Waveform FFT
Zoomed FFT on Instrument Shows more precise frequency and resolution
Viewed at PC Note delta cursors to determine approximate frequency Wet End - Breast Roll - Tending Side Axial - Vel Time 400 ms 1/16/2008 10:14:34 AM Location Note (9/5/2007 12:34:27 PM) Cursor A: 0.037 secs 0.075 in/s Cursor B: 0.061 secs 0.074 in/s 0.08 Diff: 0.025 secs -0.001 in/s Diff: 2435.714 CPM O/All 0.079 in/s 0-pk 0.06 0.04 0.02 in/s 0 -0.02 -0.04 -0.06 -0.08 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 secs 1/16/2008 10:14:34 AM O/All 0.079 in/s 0-pk <set RPM>
Viewed at PC Interpolated running frequency Wet End - Breast Roll - Tending Side Axial - Vel Freq 60000 CPM 1/16/2008 10:40:31 AM Location Note (9/5/2007 12:34:27 PM) Cursor A: 2417.776 CPM 0.081 in/s 0.08 O/All 0.083 in/s 0-pk 0.07 0.06 0.05 in/s 0-pk 0.04 0.03 0.02 0.01 0 0 10,000 20,000 30,000 40,000 50,000 60,00 CPM 1/16/2008 10:40:31 AM O/All 0.083 in/s 0-pk <set RPM>
Setup Parameters - TWF Note the settings and calculated equivalent Fmax value and estimated time.
Setup Parameters - FFT Note the settings and estimated time.
Examples of Field Problems Ski-Slope-PoorCon n ection-H oriz on tal-VelSpec60000CPM 8/30/20059:09:04PM 0.012 O /All 0.01 5in/s 0-p k 0.01 Loose or faulty connections 0.008 Ski-Sloped uetopoo r connectionacro ss senso r/cable/v b. Inspect theconnections. in/s 0-pk 0.006 0.004 0.002 N otethelowa m plitudeof all oth er freque ncies 0 0 10,000 20,000 30,000 40,000 50,000 60,000 C P M 8 /30/20059:09:04PM O /A ll 0.015in/s0-pk <s et R PM >
Examples of Field Problems Ski-Slope-Satu ration-H oriz on tal-VelSpec60000CPM 9/12/20059:29:25PM O /All 2.156in/s 0-pk 0.5 Impacting and saturation 0.4 0.3 Ski-Slopeduetosignal saturation(im pactingof sensor) in/s 0-pk 0.2 N otethehighO /All m agnitudecom paredtothelowam plitudeof all other frequencies 0.1 0 0 10,000 20,000 30,000 40,000 50,000 60,000 C P M 9/12/20059:29:25PM O /A ll 2.156in/s0-pk
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